85 research outputs found

    Patterns of ambulatory care utilization in Taiwan

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    BACKGROUND: We used the insurance claims of a representative cohort to quantify the patterns of ambulatory care visits, especially the doctor-shopping phenomenon, in Taiwan. METHODS: The ambulatory visit files of the 200,000-person cohort datasets from the National Health Insurance Research Database in 2002 were analyzed. Only a visit with physician consultation would be considered. We computed the visit patterns both by visit count and by patient count. RESULTS: In 2002, there were 182,474 eligible people with 2,443,003 physician consultations. During the year, 87.4% of the cohort had visited physician clinics and 57.5% had visited hospital-based outpatient or emergency departments. On average, a person had 13.4 physician consultations and consulted 3.4 specialties, 5.2 physicians, and 3.9 healthcare facilities in a year. In 2002, 17.3% of the cohort had ever visited different healthcare facilities on the same day; 23.5% had ever visited physicians of the same specialty at different healthcare facilities within 7 days and the percentage of second visits was 3.8% of all visits. Besides, 7.6% of the cohort had visited two or more specialties at the same facility on the same day, and such visits make up 2.5% of all visits. CONCLUSION: The people in Taiwan did visit the physicians and outpatient departments frequently. Many patients not only consulted several physicians of different specialties and at different healthcare facilities during the year, but also switched the physicians and facilities quickly. An effective referral system with efficient data exchange between facilities might be the solution

    Screening for pickiness - a validation study

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    Picky eating is prevalent in childhood and is associated with negative health outcomes. Therefore early detection of pickiness is pertinent. Because no psychometric measure of picky/fussy eating has been validated, we aimed to examine the screening efficiency of the 6-item ‘Food Fussiness’ (FF) scale from the Children’s Eating Behavior Questionnaire using structured psychiatric interviews (the Preschool Age Psychiatric Interview), providing meaningful cut-off values based on a large, representative sample of Norwegian 6 year olds (n = 752). Screening efficiency was evaluated using receiver operating characteristic curve analysis, revealing excellent discrimination. The cut-point maximizing the sum of sensitivity and specificity for the scale was found at a score of 3.33 for severe cases and 3.00 when both moderate and severe pickiness were included. The results suggest that the FF scale may provide a tool for identification of clinically significant picky eating, although further assessment may be needed to separate moderate from severe cases

    Relationship between BMI and emotion-handling capacity in an adult Finnish population: the Northern Finland Birth Cohort 1966

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    Background Alexithymia, a difficulty in identifying and expressing emotions, has been associated with obesity and eating disorders in small-scale cross-sectional studies. Here, we assess the relationship between body mass index (BMI) and alexithymia in a large cohort of free-living Finnish adults over a 15-year period. Methods Participants were drawn from the Northern Finnish Birth Cohort 1966 (NFBC1966). The 20-Item Toronto Alexithymia Scale (TAS-20) was used as a measure of alexithymia and was completed at the age of 31 years (31y: n = 4841), and 46 years (46y: n = 5404). BMI was recorded at both time points. Where data at both time points were available (n = 3274), the relationship between changes in BMI and TAS-20 over this time period was also investigated. Results BMI was significantly and positively associated with TAS-20 score (p<0.0001, both at 31 years and at 46 years of ages). The association remained statistically significant after adjustment for potential confounders (sex, marital status and several socio-economic indicators). In individuals who experienced the greatest change in BMI (in either direction) over the 15-year period, there was a modest mean increase in TAS-20 score. Conclusions Our data revealed that TAS-20 score was correlated with and co-varied with body mass status. We suggest that future clinical research should consider the role of alexithymia in obesity. Further investigation of this relationship is warranted to ensure that the needs of obese subjects with undiagnosed alexithymia are considered in the design of weight management programmes

    Appetitive Traits associated with Higher and Lower Body Mass Index: Evaluating the Validity of the Adult Eating Behaviour Questionnaire in an Australian Sample

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    Background: The aims of this study were to evaluate the factor structure of the newly developed Adult Eating Behaviour Questionnaire (AEBQ) (Hunot et al., Appetite 105:356-63, 2016) in an Australian sample, and examine associations between the four food approach and four food avoidance appetitive traits with body mass index (BMI). Methods: Participants (N = 998) recruited between May and October 2016 via a university research participation scheme and online social network sites completed an online version of the AEBQ and self-reported demographic and anthropometric data. Of the sample, 84.8% were females, 29.6% had completed a university degree and the overall mean age was 24.32 years (SD = 8.32). Confirmatory factor analysis (CFA) was used to test three alternative factor structures (derived from issues raised in the original development study): the original 8 factor model, a 7 factor model with Food Responsiveness and Hunger scales combined, and a 7 factor model with the Hunger scale removed. Results: The CFA revealed that the original 8 factor model was a better fit to the data than the 7 factor model in which Food Responsiveness and Hunger scales were combined. However, while reliability estimates for 7 of the 8 scales were good (Cronbach’s α between 0.70-0.86), the reliability of the Hunger scale was modest (0.67) and dropping this factor resulted in a good fitting model. All food avoidance scales (except Food Fussiness) were negatively associated with body mass index (BMI) whereas Emotional Overeating was the only food approach scale positively associated with BMI. Conclusions: The study supports the use of the AEBQ as a reliable and valid measure of food approach and avoidance appetitive traits in adults. Longitudinal studies that examine continuity and stability of appetitive traits across the lifespan will be facilitated by the addition of this measurement tool to the literature

    Child and parent predictors of picky eating from preschool to school age

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    Background: Picky eating is prevalent in childhood. Because pickiness concerns parents and is associated with nutrient deficiency and psychological problems, the antecedents of pickiness need to be identified. We propose an etiological model of picky eating involving child temperament, sensory sensitivity and parent-child interaction. Methods: Two cohorts of 4-year olds (born 2003 or 2004) in Trondheim, Norway were invited to participate (97.2% attendance; 82.0% consent rate, n = 2475) and a screen-stratified subsample of 1250 children was recruited. We interviewed 997 parents about their child’s pickiness and sensory sensitivity using the Preschool Age Psychiatric Assessment (PAPA). Two years later, 795 of the parents completed the interview. The Children’s Behavior Questionnaire (CBQ) was used to assess children’s temperament. Parent- child interactions were videotaped and parental sensitivity (i.e., parental awareness and appropriate responsiveness to children’s verbal and nonverbal cues) and structuring were rated using the Emotional Availability Scales (EAS). Results: At both measurement times, 26% of the children were categorized as picky eaters. Pickiness was moderately stable from preschool to school age (OR = 5.92, CI = 3.95, 8.86), and about half of those who displayed pickiness at age 4 were also picky eaters two years later. While accounting for pickiness at age 4, sensory sensitivity at age 4 predicted pickiness at age 6 (OR = 1.25, CI = 1.08, 2.23), whereas temperamental surgency (OR = 0.88, CI = 0.64, 1.22) and negative affectivity (OR = 1.17, CI = 0.75, 1.84) did not. Parental structuring was found to reduce the risk of children’s picky eating two years later (OR = 0.90, CI = 0.82, 0.99), whereas parental sensitivity increased the odds for pickiness (OR = 1.10, CI = 1.00, 1.21). Conclusions: Although pickiness is stable from preschool to school age, children who are more sensory sensitive are at higher risk for pickiness two years later, as are children whose parents display relatively higher levels of sensitivity and lower levels of structuring. Our findings suggest that interventions targeting children’s sensory sensitivity, as well as parental sensitivity and structuring, might reduce the risk of childhood pickiness. Health care providers should support parents of picky eaters in repeatedly offering unfamiliar and rejected foods to their children without pressure and acknowledging child autonomy

    The relationship between appetite and food preferences in British and Australian children

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    Background: Appetitive traits and food preferences are key determinants of children’s eating patterns but it is unclear how these behaviours relate to one another. This study explores relationships between appetitive traits and preferences for fruits and vegetables, and energy dense, nutrient poor (noncore) foods in two distinct samples of Australian and British preschool children. Methods: This study reports secondary analyses of data from families participating in the British GEMINI cohort study (n = 1044) and the control arm of the Australian NOURISH RCT (n = 167). Food preferences were assessed by parent-completed questionnaire when children were aged 3–4 years and grouped into three categories; vegetables, fruits and noncore foods. Appetitive traits; enjoyment of food, food responsiveness, satiety responsiveness, slowness in eating, and food fussiness were measured using the Children’s Eating Behaviour Questionnaire when children were 16 months (GEMINI) or 3–4 years (NOURISH). Relationships between appetitive traits and food preferences were explored using adjusted linear regression analyses that controlled for demographic and anthropometric covariates. Results: Vegetable liking was positively associated with enjoyment of food (GEMINI; β = 0.20 ± 0.03, p < 0.001, NOURISH; β = 0.43 ± 0.07, p < 0.001) and negatively related to satiety responsiveness (GEMINI; β = -0.19 ± 0.03, p < 0.001, NOURISH; β = -0.34 ± 0.08, p < 0.001), slowness in eating (GEMINI; β = -0.10 ± 0.03, p = 0.002, NOURISH; β = -0.30 ± 0.08, p < 0.001) and food fussiness (GEMINI; β = −0.30 ± 0.03, p < 0.001, NOURISH; β = -0.60 ± 0.06, p < 0.001). Fruit liking was positively associated with enjoyment of food (GEMINI; β = 0.18 ± 0.03, p < 0.001, NOURISH; β = 0.36 ± 0.08, p < 0.001), and negatively associated with satiety responsiveness (GEMINI; β = −0.13 ± 0.03, p < 0.001, NOURISH; β = −0.24 ± 0.08, p = 0.003), food fussiness (GEMINI; β = -0.26 ± 0.03, p < 0.001, NOURISH; β = −0.51 ± 0.07, p < 0.001) and slowness in eating (GEMINI only; β = -0.09 ± 0.03, p = 0.005). Food responsiveness was unrelated to liking for fruits or vegetables in either sample but was positively associated with noncore food preference (GEMINI; β = 0.10 ± 0.03, p = 0.001, NOURISH; β = 0.21 ± 0.08, p = 0.010). Conclusion: Appetitive traits linked with lower obesity risk were related to lower liking for fruits and vegetables, while food responsiveness, a trait linked with greater risk of overweight, was uniquely associated with higher liking for noncore foods

    Learning to Eat Vegetables in Early Life: The Role of Timing, Age and Individual Eating Traits

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    Vegetable intake is generally low among children, who appear to be especially fussy during the pre-school years. Repeated exposure is known to enhance intake of a novel vegetable in early life but individual differences in response to familiarisation have emerged from recent studies. In order to understand the factors which predict different responses to repeated exposure, data from the same experiment conducted in three groups of children from three countries (n = 332) aged 4–38 m (18.9±9.9 m) were combined and modelled. During the intervention period each child was given between 5 and 10 exposures to a novel vegetable (artichoke puree) in one of three versions (basic, sweet or added energy). Intake of basic artichoke puree was measured both before and after the exposure period. Overall, younger children consumed more artichoke than older children. Four distinct patterns of eating behaviour during the exposure period were defined. Most children were “learners” (40%) who increased intake over time. 21% consumed more than 75% of what was offered each time and were labelled “plate-clearers”. 16% were considered “non-eaters” eating less than 10 g by the 5th exposure and the remainder were classified as “others” (23%) since their pattern was highly variable. Age was a significant predictor of eating pattern, with older pre-school children more likely to be non-eaters. Plate-clearers had higher enjoyment of food and lower satiety responsiveness than non-eaters who scored highest on food fussiness. Children in the added energy condition showed the smallest change in intake over time, compared to those in the basic or sweetened artichoke condition. Clearly whilst repeated exposure familiarises children with a novel food, alternative strategies that focus on encouraging initial tastes of the target food might be needed for the fussier and older pre-school children
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